Mean field approach to antiferromagnetic domains in the doped Hubbard model

TL;DR

This paper introduces a generalized mean field approach using a restricted path integral to study antiferromagnetic domains in the doped Hubbard model, revealing coexistence of AF order and metallic behavior.

Contribution

It develops a systematic mean field method based on restricted path integrals, capturing multiple saddle points and phase coexistence in the doped Hubbard model.

Findings

Identification of two relevant saddle points: AF order and no AF order.

Existence of a phase with coexisting AF order and metallic behavior.

Framework for systematic refinement of the approximation.

Abstract

We present a restricted path integral approach to the 2D and 3D repulsive Hubbard model. In this approach the partition function is approximated by restricting the summation over all states to a (small) subclass which is chosen such as to well represent the important states. This procedure generalizes mean field theory and can be systematically improved by including more states or fluctuations. We analyze in detail the simplest of these approximations which corresponds to summing over states with local antiferromagnetic (AF) order. If in the states considered the AF order changes sufficiently little in space and time, the path integral becomes a finite dimensional integral for which the saddle point evaluation is exact. This leads to generalized mean field equations allowing for the possibility of more than one relevant saddle points. In a big parameter regime (both in temperature and filling), we find that this integral has {\em two} relevant saddle points, one corresponding to finite AF order and the other without. These degenerate saddle points describe a phase of AF ordered fermions coexisting with free, metallic fermions. We argue that this mixed phase is a simple mean field description of a variety of possible inhomogeneous states, appropriate on length scales where these states appear homogeneous. We sketch systematic refinements of this approximation which can give more detailed descriptions of the system.